In classical logic, a variety of procedures based on logical operations and rules of inference have been developed to proceed from basic premises to logical conclusions. Moreover, these procedures have been the bases for electronic computers that have revolutionized our way of life. These computers typically are based on Boolean algebra and logic depend on quantized binary digits as the input signals and are not well adapted to manipulate input premises that are fuzzy and with a variable range of truth value.
However, in recent years, in response to the need to be able to reach relatively well-defined conclusions with relatively ill-defined or inexact input information, there have been a number of proposals for fuzzy computers or fuzzy information processing systems. Various applications have been proposed for such fuzzy information processing systems, often in control systems where noise and other variables make it impractical to use highly precise signal values.
One such proposal is described in U.S. Pat. No. 4,875,184 which issued on Oct. 17, 1989 to T. Yamakawa and discloses apparatus described as a fuzzy-inference engine that is designed for use as a fuzzy logic computer. As described therein, the computer is quite complex and appears to depend in reaching conclusions on a large memory of assumed relationship values and a form of interpolation of such values.
Moreover, considerable work appears to have been done on developing circuits and components useful for such computers and many are described by T. Yamakawa in a paper entitled "Fuzzy Hardware Systems of Tomorrow" that appeared in a book edited by E. Sanchez and L. A. Zadek entitled "Approximate Reasoning in Intelligent Systems, Decision and Control" published by Pergamon Press (London) 1987. In this paper, nine different fuzzy logic functions are defined in terms of two basic membership functions.
These prior art approaches have tended to depend primarily on detailed input information with little reliance on inferential assumptions and consequently have tended to be complex with a need for very large memories for the storage of detailed information about the relationships between the various components of the information being processed.
The present invention seeks to simplify such complexity and to this end relies more heavily on inferences made with less detailed information at the expense of sometimes concluding no inference is possible from the given antecedents.